International Journal of Engineering and Techniques - Volume 1 Issue 3, May - June 2015 RESEARCH ARTICLE
OPEN ACCESS
Child activity monitoring using sensors Mr. D K Kamat1, Ms. Pooja S Ganorkar2 , Mrs. R A Jain3 1(Asst Prof, E&TC department, Sinhgad Academy of Engineering, Kondhwa(BK), Pune and Research Scholar SCOE, Pune) 2(Savitribai Phule Pune University, E&TC department, Sinhgad Academy of Engineering, Kondhwa(BK), Pune) 3(Asst Prof, E&TC department, Sinhgad Academy of Engineering, Kondhwa(BK), Pune)
Abstract: This paper presents the activities of children in Epilepsy in which a person has repeated or recurrent seizures over time. In this, the particular person suffers from symptoms such as violent shaking, non controllable jerky movements of the arms and legs, loss of alertness etc. But in the proposed model, we are using the wearable sensors which will be worn on the brain and palms to detect the epileptic attacks and the GSM is used so that the message is send through mobile to their relatives or friends that an attack has occurred. Proper medicines can cure this disorder so we are going to suggest medicines according to the type of seizure. The readings will be displayed on flex grid. The sensors include two 3-axis accelerometer sensors, temperature sensor, moisture sensor. This model will utilize the ARM LPC2138 processor and the programming will be developed in keil3. Software includes Visual Basics. So we will be doing the monitoring as the seizure will be detected and their parents or relatives will be knowing about it. We are going to detect generalized tonic clonic seizures, absence seizures.
Keywords — Epilepsy, flex grid, GSM, sensors, types of seizures.
I.
INTRODUCTION
In recent years, automatic identification of human activities has drawn much attention due to the increasing demands from various applications such as surveillance system, entertainment systems and healthcare systems. The automatic detection of abnormal activities, for example automatic reporting of a person with a bag hanging around at the station or airport, can be used to alert the related authority about the dangerous activity in surveillance system. Similarly, in an entertainment system, the automatic activity recognition can be used to improve the interaction of human with the computer. Further, in healthcare systems, the activity recognition can be used to help the patients, such as identifying a dangerous activity performed by a patient. Although various activity recognition methods have been reported, the human activity recognition is one of the difficult issues in terms of perfect recognition.
ISSN: 2394-2231
Epilepsy is the disorder in which the person suffers from various types of seizures. In this, the person gets an attack and it may lasts from seconds to minutes. Forty-five million people all over the world have epilepsy, and each year 125,000 to 150,000 people are newly diagnosed with the condition in the United States. About 30 percent of these are children. The person can injure himself when he gets an attack and he may get serious. So this disease may lead to death [2]. Generalized tonic–clonic seizures (GTCS), especially when not taken care, they are related with an increased risk of injuries, and also for unexpected sudden death in epilepsy which came to know by [5],[7]. Some EEG based seizure detection algorithms are there, and implemented in many epilepsy monitoring units, but only a few patients were allowed to use EEG electrodes on a long-term basis for signal acquisition [11]. Previous studies for the detection of convulsive seizures based on accelerometer signals alone [6],[8],[10] or in combination with other modalities [4],[9] showed promising results. But all of those studies contains
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